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ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs., , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 25303-25336. PMLR, (2023)Discovering Diverse Nearly Optimal Policies withSuccessor Features., , , , , and . CoRR, (2021)Iterated approximate value functions., , and . ECC, page 3882-3888. IEEE, (2013)Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding., , , and . J. Optimization Theory and Applications, 169 (3): 1042-1068 (2016)Performance Bounds and Suboptimal Policies for Multi-Period Investment., , , and . Found. Trends Optim., 1 (1): 1-72 (2014)The Uncertainty Bellman Equation and Exploration., , , and . CoRR, (2017)Combining policy gradient and Q-learning., , , and . ICLR (Poster), OpenReview.net, (2017)Sample Efficient Reinforcement Learning with REINFORCE., , , and . AAAI, page 10887-10895. AAAI Press, (2021)The Neural Testbed: Evaluating Joint Predictions., , , , , , , , , and . NeurIPS, (2022)Reward is enough for convex MDPs., , , and . NeurIPS, page 25746-25759. (2021)